Asian Journal of Business Management 2(3): 48-56, 2010
ISSN: 2041-8752
© M axwell Scientific Organization, 2010
Submitted Date: February 26, 2010
Accepted Date: March 18, 2010
Published Date: September 30, 2010
Factors Influencing Purchase of ‘NANO’ the Innovative Car from India-An
Empirical Study
R.D. Bikash, S.K. Pravat and Sreekumar
Rourkela Institute of Management Studies, Gopabandhu Nagar, Chhend
Rourkela-7690 15, O rissa, India
Abstract: This study attempts to find the factors, which are important for choosing the revolutionary car ‘Nano’
launched by one of the leading Indian automobile industry called ‘Tata Motors’. The year 2009 has been
significant for Indian automobile industry as numbers of new models were launched for the domestic market
and also registered a significant growth in exports. The report published by Cyg nus research ranked Indian
autom obile sector to be nu mbe r one o n the basis of sales gro wth and P rofit After Tax (PAT) growth during
Octob er- Dece mber 09 over O ctober- December 08 ov er other 14 m anufacturing sectors. The p aper considers
22 factors, wh ich may be impo rtant in the customer d ecision -mak ing pro cess. T wo appro ache s viz. G rey
Relational Analysis and RIDIT analysis is used to rank the factors.
Key w ords: Autom obile, grey relational analysis, nano, RID IT
INTRODUCTION
India has become a fast-growing auto market over the
past decade. G rowth has been driven by rap id econom ic
grow th and increasing wealth-double-digit average wage
gains over the past decade and more than a three-fold
surge in equity markets. The growth in Indian economy
encounters the growth in industrial production. According
to the Society of Indian Automobile Manufacturers
(SIAM ), the Indian automo bile industry has maintained a
steady growth of 20% till May 2005. The industry
curren tly contributes about 5% of the G DP and it is
targeted to grow fivefold by 2016 and accoun t for a
geographically diversification.
The development in automobile sector overhauls the
perception of potential car buyers, with their increased
disposable income, enormous information search, and
availability of lucrative financial options. People today are
more pragmatic before acqu iring the autom obile.
For most people, purchasing a car is one of the most
important and expensive investmen t, next to purchase of
a house; for the automotive manufacturers, first-time car
buyers give them the opportunity to create positive brand
image which definitely could be reflected on in next
com ing years because consumers could make repeat car
purchasing. The small car market changed ve ry rapid ly
due to the fierce competition and advanced technology;
therefore, it requires the automotive manufacturers and
car dealers to understand the consumers’ preference on
time and take fast actions to reflect market changes
quickly. So, it would be very interesting to know
consumers’ preference in today’s fast-changing small car
mark et. In this co ntext this study is carried ou t to
understand how the customers’ buying process is, what
the critical elements of making their purchasing decision
for the innovative ca r “Na no”.
Review of Indian automobile industry: The last few
years have witne ssed revolu tionary changes in the
management systems and manufacturing innovations of
the world automotive industry. A proprietary study
conducted by McK insey and the Associated Chambers of
Commerce and Industry of India (summ arized in PTI,
April 18, 2005 ; New swee k International N ovem ber 28,
2005, and the Financial Times, December 1, 2005)
estimates that by 2015 glob al auto production is likely to
reach $1.9 trillion dollars, of which around $700 billion
dollars will be pro duced in low cost countries. The United
Nations Development Program (UNDP) report hailed
India as a powerful force in the global automo bile
industry, and recognized that it has the streng th to sustain
leadership and growth in the face of the global trading
order. The growth in Indian economy encounters the
grow th in industrial production. According to the Society
of Indian Automobile Manufacturers (SIAM), the Indian
automobile industry has maintained a steady growth of
Corresponding Author: Sreekumar, Rourkela Institute of Management Studies, Gopabandhu Nagar, Chhend Rourkela-769015,
Orissa, India
48
Asian J. Bus. Manage., 2(3): 48-56, 2010
20% till May 2005. The industry currently contributes
about 5% of the GDP and it is targ eted to grow fivefold
by 2016 and account for a geographically diversification.
The growth curve of India Auto Inc . has been on an
upswing for the past few years. In addition to matching
comp etitor’s new products and upgraded machinery,
technology is over 10% of India’s GD P. Automotive
Mission Plan (AMP) expects the industry to reach a
turnover of $150-200 billion in the next ten years from the
current $45 billion levels. Over the last five years the
production of four wheelers in India has increased from
9.3 lakh units in 2002-03 to 23 lakh units in 2007-08
reporting a CAGR of 20%.
The Indian car manufactures are today serving a wide
variety of transportation solutions across, different load
levels. T here is a drastic growth in sales and distribution
setup, which enables the automobile company to ensure
playing a vital role. Moreover the com pany’s pro ximity to
their raw material and com ponent suppliers help them in
reducing procuremen t costs. Autom obile man ufacturers
have clearly committed themselves to supply the market
with ever safer and more environment friendly products
and are continuously inve sting huge R& D resourc es in
further product improvements and in developing radically
new propulsion systems. The following section discusses
the development of Indian automotive industry.
company. The period prior to the entry of Maruti Udyog
Ltd was ch aracterized by small num ber of auto m ajors
like Hindustan Motors, Premier Automobiles, Telco,
Bajaj, and Mahindra and Mahindra. However,
cum ulatively political and social forces gave way to a
curious partnership between the Govt. of India and Suzuki
Motors of Japan in the early 1980s (D’Costa, 1995b). The
government owned appro ximately 80% of the equity. For
the first time India became an investor in a car project and
in a successful monopoly (D’Costa, 1995b). This was
marked as the beginning of the sec ond phase of the auto
industry. The auto industry in the co untry really showed
a spurt in growth during this period. This period
witnessed the emergence of a new gene ration of auto
manu facturers who were required to meet the stringent
quality standard of Maruti’s collaborator Suzuki of Japan.
The good performance of Maruti resulted in an upswing
for the domestic autom obile industry. This Joint V enture
(JV) resulted in a significant addition to the country’s car
production volume, which helped satisfy the unmet
consumer demand. The JV served another important
function: by brin ging in cars at a low cost that were based
on mod ern (an d fuel-efficient) au tomo bile tech nolog y, it
galvanized the existing Indian firms to start upgrading
their own technology, thereby initiating a modernization
of the Indian passenger car industry. The other major
Indian manufacturers also all moved to upgrade their own
offerings, catalyzed partly by Maruti’s entry into the
Indian car market: H M entered into collaboration w ith
Isuzu of Japan for the manufacture of gasoline and diesel
engines and powe r-train assemblies, and w ith Va uxhall of
the United Kingdom for design and tooling technology,
which in turn led to prod uction of a new model called
Contessa (a derivative of the Vauxhall Victor). Premier
Auto Limited (PA L) entered into a tech nical agreement
with Nissan of Japan for their A-12 engine and matching
transmission, which was placed in a Fiat 124 body. PAL
also entered with a consultancy agreement with AVL of
Austria to improve its existing gasoline engine, and
through an acquisition , an arrangemen t with F NM of Italy
for diesel engines (leading to a diesel car being offered in
1989) (Mohanty et al., 1994). Standard Motors began
offering a luxury car, the R over 2000, in collaboration
with A ustin Rov er of the U.K . (Venka tramani, 1990).
In the year 1991, when India moved away from an
inward looking industrialization strategy to a more ‘open’
economy (Narayanan, 2001), a newly elected Indian
government took over and faced with a balan ce-ofpaymen ts crisis initiated a series of econom ic
liberalization measures designed to open the Indian
economy to foreign investment and trade. The
Emergence of the Indian auto industries: The auto
industry traced in India can be classified into three distinct
phases namely: Period prior to the entry of Maruti
Udhyog Ltd, period after the entry of M aruti U dhyog Ltd
and Period post Liberalization (Kathuria, 1990). The
Indian auto industry has come a long way since 1940 s.
Since its independence in 1947, India has pursued,
initially, a strong anti-imperialist automobile economic
policy by pro moting self-reliance (D’C osta, 1995a). This
policy established a basic industrial foundation and a
technical-education infrastructure to sustain future
growth. This fell behind the global technology frontier
due to increasingly autarkic and sometimes dysfunctional
policies (Bhagwati, 1993). India was characterized by a
slow -grow ing, high-cost economy with shoddy and scarce
products. Subsequently, since the 1980s, various
economic and industrial sectors were gradually and
selectively deregulated, privatized, and internationalized
(D’C osta, 2006).
The evolu tion of this econ omic nationalism has been
devised to prom ote domestic business and increasingly to
sustain their glo bal competitiveness. The key
breakthrough occurred in the year1982. The Government
of India created Maruti Udyog Limited, a public sector
49
Asian J. Bus. Manage., 2(3): 48-56, 2010
governm ents play a key ro le in sha ping th e grow th of the
auto industry in emerging econ omies (A msden and
Kang 1995). There for the Government of India revisited
its Industrial Policy and allowed for capacity expansion as
well as entry of foreign capital and firms. In this situation
the Indian autom obile industry need s to restructure itself
to retain co mpe titiveness. The new autom obile policy
announced in 1993 included removal of licensing
restrictions on production, automatic approval of foreign
investment up to 51% in Indian firms opening the doors
for foreign firms to e nter the Indian mark et (subject to
government approval, up to 100% foreign equity
participation
was
also
allowed)
(Sagar
and
Chandra, 2004). The government followe d up its
liberalization measures with significant reductions in the
import duty on automobile compone nts. These measures
have spurred the growth of the Indian economy in general,
and the automo tive industry in particular. Since 1993, the
automotive industry has been experiencing growth rates
of above 25%. Prior to the delice nsing of this sector in
1993, customers could purchase just three models: one
made either by Hindustan Motors, Maruti-Suzuki or
Premier Automobiles. By 1996, a total of eighteen
autom obile companies from the US, Europe, and East
Asia had began operations in India (Mukherjee and
Sastry 1996).
The entry of foreign automobile manufactures
ranging from Mercedez, Ford and Genera l Motors to
Daewoo following the government liberalizing the foreign
investment limits saw the beginning of the third phase of
the evolution of the industry. The auto industry witnessed
huge capacity expansions and mod ernization initiative s in
t h e post libe ralization period . T ech nological
collaborations and equity partnerships with w orld leaders
in auto components became a com mon affair. Th is
increasing success in turn gav e India confid ence to
accelerate liberalization .
In 2001 the Government of India (GOI) lifted
virtually all restrictions on direct foreign investment in the
auto industry. Indian passenger car production, barely
over 200,000 units in 1 993-94, do ubled to just over a halfmillion units in 2000-01. In the next four years, the
production nearly doubled again, topping one million
vehicles in 2004-05, and hitting 1.3 million vehicles in
2005-06 including utility vehicles and MPV s (Eco nom ic
Times April 29, 2006). Annual sales have seen an
increase by over a multiple of 5, from around 320,000
units in 1996 to 1.7 million in 2008, thanks to a
combination of rising per capita incomes, relatively easier
availability of finance and young demographics
(SIAM, 2008). This sector as a whole has emerged as a
significant engine of growth for the Indian economy.
India is on every car manufacturer’s map. The
Automotive Mission Plan 2006-2016 has set an ambitious
turnover target of $145 billion for the industry from a
modest $38 billion today (Narayanan and Vashisht, 2008).
So the Indian automo bile industry is playing a pivotal
role on the Indian Economy and also redefining the
lifestyle of Indian consumers. In this context the Indian
Automobile sector is also increasingly adopting an
outward looking approach and exploring new markets and
territories.
Understanding Small car ma rket: The Indian
autom obile industry has seen rapid change over the last
decade in terms of both product characteristics as well as
manufacturing processes. The focus has tilted away from
volumes to a lower cost model as espoused by the
emerging markets. This eventually led to a transformation
of the Indian market towards “small” and “mini” cars.
Maruti Udyog Limited (MUL) dom inated sales in “mini”
segment (less than 340 cm length, generally less than 800
cc engine disp lacemen t) (Sagar and C handra, 2004). In
the year 1996, MUL had approximately 80% of the
country’s car market share.
The reason can be attributed to the fact that many of
the earlier entrants into the Indian car market did not
target these segments. Furthermo re, M UL was able to
offer its vehicles at a very com petitive price since it had
relatively high indigenization levels, an established
vendor base, and a depreciated plant (ICRA , 2003a). But
it has lost significant ground with the entry of Hyundai
Motor India Limited (HMIL) with its line-up of small
cars. These compact or small sized cars are
techn ologically advanced and offer greater number of
features (ICR A, 2003b). The launch of Tata Motors’
Indica in the year 2003-04, another small car, drastically
reduced Maruti’s domestic sales to just over 51%.
Hyundai and T ata account for approximately 19 and 16%
respectively during this period. Thus Indian car market is
heav ily skewed towards mini and compact vehicles, this
segment alone account for about 80% of the car sales in
the country Table 1.
Today, the small car segment is a sunrise sector, as
new car registrations have grow n from 625,000 in 200 1 to
over 1.3 million in 2006. The sub-1500 cc or 'mini and
compact car' segments account for over 66% of new sales
(KPMG, 2007). Rising incomes level of middle class,
heterogeneous consumer preference, better financing for
vehicles are the reasons driving this growth. The Annual
K PM G International rep ort suggests that it is the small car
50
Asian J. Bus. Manage., 2(3): 48-56, 2010
Table 1: Passenger vehicle sales and exports, 2003-04
Passenger vehicles
Domestic sales
Ex por ts
Passen ger C ars
696,207
125,327
Mini
167,565
10,479
Comp act
369,537
84,077
Mid-size
139,304
30,739
Executive
14,337 0
Premium
5,368
32
Lux ury
96
0
Utility vehicles
144,981
3,067
Multi purpose vehicles
59,564 922
Total
900,752
129,316
S ou rc e: S oc ie ty of In dia n A uto mo bile M an ufa ctu re rs (S IA M )
Table 2: A uto affordability forecast
Segment
Pric e (U SD '00 0')
S eg m en t A 1 an d A2
6.2 5-1 2.5
(M ini an d co mp act)
S eg m en t A 3 an d A4
12 .5-3 0.0
(Mid Size and Executive)
Segment A5 and A6
Ov er 3 0.0
(Premier and Luxury)
Sou rce: KP M G In ternationa l (2007 )
Rs 1.5 lakh car. Nissan Renault CEO Carlos Ghosn
commented, "We w ill be part of this competition and we
are investigating at the level of the alliance, how we can
make a $3,000 car”.
Tata Moto rs h as already unveiled th e w orld's
cheapest passenger car "Nano" for around US$2,500. Tata
Nano gives a fuel efficiency of 23.6km pl (under stand ard
test condition), the highest among all petrol-run cars in the
country. Nan o is 3.1 m (10.23 feet) long, 1.5 m wide and
1.6 m high and can accommodate four to five people.
Nano with its two cylinder 623 cc, 33 horsepower rear
mounted Multi-Point Fuel Injection (MPFI) petrol engine
can touch the top speed of 105 Km. Nano surpasses
Indian regulatory requirements and Euro IV emission
norms and guarantee less polluting than most of the bikes
on Indian roads. W ith the launch of Tata Nano, the stage
is set for around a dozen n ew small and comp act cars to
be launched in India in the next tw o yea rs. It is in this
context this study is carried out to understand the Indian
consumers mind towards the smallest car Nano.
2 00 5 (% ) 2 00 9 (% )
35.06
48.46
8.9
14.53
2.43
4.5
segment that will continue to dominate the passenger car
mark et, with almost 50 per cent of househo lds being ab le
to afford a sma ll car by 2009 (Table 2).
The Indian car industry is overflowing with small
cars and automobile manufacturer in India are investing
accordingly. According to Mr. P Balendran, Vice
President (Corporate Affairs), “Gen eral Mo tors India, the
grow th is happening on ly in the small ca r segm ent. People
buying small cars are very cost conscious. General M otors
is planning to launch its second small car in India in the
800-900 cc seg men ts. The com pact car will be unv eiled in
2010”. Acco rding to Hiroshi Nakagawa, India head of
Toy ota Kirloskar M otors, “Small cars play a very
important role and cover as much as 75 per cent of car
volumes in India and currently does not include in Toyota
Kirloskar’s portfolio. Toyota had announced Rs 1,400
crore investment to launch a 'strategic small car' for the
Indian market by 2010. The entry car will be enhanced
with below 1200-cc in petrol and below 1500cc in diesel”.
The Xenitis group Chairman, Santanu Ghosh said the
company will be launching an affordable four wheeler car
that is priced lower than INR 1 lakh w hich is
approxim ately equivalent to U S$ 2000. Another auto
major, Peugeot Motor Company from France, is also
planning to enter the small car market in India by 2011. It
is com ing to India with a spacious five-seater car, which
is designed especially to cater the whopping small car
consum ers of India. Hyundai is also gearing up to launch
a small car for 3,500 dollar (over Rs 1.45 lakh) by 2011.
Nissan Ren ault is expected to team up with Indian
man ufactu rer M ahind ra and Mahind ra to promote a sub-
Factors influencing car purchase: A study by Lang
motors (2007) found a list of 20 factors to be the most
important factors that influence purchase of car. They are
as follow s 1 - Reliability / D epen dability, 2 - Exterior
Styling, 3 - Price / Cost to Buy, 4 - Interior Comfort, 5 Value for the Money, 6 - Fun to Drive, 7 - Reputation of
the Manufacturer, 8 - Quality of Workmanship, 9 - Engine
Performance, 10 - Road-holding / Handling, 11 - Fuel
Economy, 12 - Storage and Cargo Capacity, 13 - Ride
Quality on Highway, 14 - Durability / Long Lasting, 15 Safety Features, 16 - Future Trade -In / Resale, 17 Length of W arranty , 18 - Rebate / Incentive, 19 Discount / Value Package, 20 - Environme ntally Friendly
Vehicle. Similarly a study by Power and associates (2005)
listed the following nine to be the most important reasons
for car purchase - 1 Styling, 2 Reliability, 3 Costs too
much, 4 Poor quality, 5 R esale v alue, 6 Too small, 7
Lacked performance, 8 Didn't offer incentives, 9 Poor gas
mileage. A study published in Anonymous (2008a) UK
found for as many as 71% of customer price was the most
important factor, followed by fuel economy, running
costs, fuel type and Vehicle Excise Duty (VED ) costs.
Similarly an article published in Anonymous (2008b)
quoted After Price; Reliability is the number one factor
for buyers. Car buyers’ rate reliability over fuel efficiency
as their primary decision makes. Fuel efficiency and
safety rank second and third in importance Performance
not a top priority for most car buyers. Th is study intends
to prioritize the important factors with reference to Nano
from Indian consumers’ point of view.
51
Asian J. Bus. Manage., 2(3): 48-56, 2010
Fleiss et al. (1979) have reported that ridit analysis
begins with the identification of a population to serve as
a standard or reference group. V irtually the only
assumption mad e in ridit analysis is that the discrete
categories represent interv als of an underlying , but
unobservable, continuous distribution. Given the
distribution of any other group over the same categories,
the mean ridit for that group may be calculated. The
resulting mean valu e is interpretable as a probability. In
summ ary, ridit analysis provides a simple alternative or
adjunct to rank order statistical analysis, and may be
viewed as adding an intuitively appealing, descriptive
element to it. The detailed algorithm of RID IT analysis is
provided in Appendix A.
MATERIALS AND METHODS
This study tries to explore the potential reasons
behind the inten tion to book a T AT A N ano. W e have used
two relatively new techniques i.e., RIDIT and Grey
Relational Analysis (G RA ) in the paper. The pu rpose is to
quantify the order of relative importance of the antecedent
reasons for selection of a TATA Nano. The review of
literature revealed the factors that affect the choice of car
purchase. The 22 indicators identified are as follows style / Look, interior design, space inside, accessories,
pow er, safety features, performance, environment
friendly, Featu res of the car fulfils requirements, attractive
colors, comfortable, price, high fuel efficiency, financing
option, running cost, resale value, warranty, value for
money, Comp anies reputation, brand name, status /
prestige, overall possession satisfaction. The country of
origin is another important factor but we have not used it,
as all the respondents were Indians. It was assumed that
the respondents are a ware abo ut the origin. A nd the re is
a question about TATA’s reputation. Using the abovementioned indicators a scale was developed to cap ture
potential consume rs’ view s. The same was administered
in two major cities of O rissa, a fast grow ing state in
Eastern part of India. Th e study was carried ou t during
summer 2009. A total of 130 responses were collected
from the field and final 108 responses were used for final
analy sis after data filteration .
Overview of the GRA: A system having incom plete
information is called Grey system. The Grey relation is
the relation with incomplete information (Chih-Hung
Tsai, 2003). The Grey relational an alysis is a highly
effective method for determining how a discrete data
sequence is related to other data sequence. Data for the
grey relational analysis must meet the following
requirements: non-dimension, scaling, and polarization.
Grey relational analysis is a method to analyze the
relational grade for discrete sequences. The grey
relational analysis is unlike the traditional statistics
analy sis handling the relation between variables. Some of
the draw back s of the later are: (i) it must have plenty of
data; (ii) data distribution must be typical; (iii) a few
factors are allowed and can be expressed functionally. But
the Grey relational analysis requires less data and can
analyze many factors that can overcome the disadvantages
of statistics method (Chih-Hung Tsai, 2003). Grey
Relational Analysis (GRA ) is used in order to build a
ranking and suggest a best choice on a set of alternatives.
Through the GRA , a Gra de R elation Grade (G RG ) is
obtained to eva luate the multiple performance
characteristics (Kuang, 2008). The detailed algorithm on
GRA is provided in Appendix B.
Overview of the RIDIT: The ridit analy sis is an acronym
(‘Relative to an Identified Distribution’) plus the
productive suffix ‘-it’ denotes a transformation”
(Bross, 1981). We m ay quote the inv entor o f this ana lysis
to understand its meaning and relevance: - “In 1950s
studies of crash-injuries in highway accidents, the
response variable used a graded scale (e.g., none, minor,
moderate, severe, fatal). The common practice in analysis
of contingency table data then (and sometimes now) was
to avoid emp ty cells by collapsing to a dichotom ous scale
(e.g., nonfatal, fatal). In an effort to avoid losing
inform ation in this way, ridit analysis is used, which
involves a simple empirical cumulative probability
transformation of the entire scale.
Tab le 3: D emo grap hic p rofile o f the s amp le
Age
20-30
No . of res pon den ts
4 0(3 7.0 3% )
Occupation
Business
No . of res pon den ts
4 4(4 0.7 % )
Family size
3
No . of res pon den ts
2 6(2 4.0 7% )
Annual Income
< 3 Lacs
No . of res pon den ts
1 4(1 2.9 6% )
RESULTS AND DISCUSSION
The sample for the study consisted of 108
respo ndents drawn from two major cities of Orissa a fast
30-40
2 8(2 5.9 2% )
Ce ntral G ovt.
1 6(1 4.8 1% )
4
5 4(5 0% )
3-5 lacs
4 5(4 1.6 6% )
40-50
3 2(2 9.6 2% )
Professional
8 (7 .4 % )
5
1 6(1 4.8 1% )
5-7 lacs
2 8(2 5.9 2% )
52
50-60
4 (3 .7 % )
Pvt. Company
3 0(2 7.7 % )
6
1 2(1 1.1 1% )
7-9 lacs
1 5(1 3.8 9% )
60-70
4 (3 .7 % )
State Government
1 0(9 .2 5% )
7
0
> 9 lacs
6 (5 .5 5% )
Asian J. Bus. Manage., 2(3): 48-56, 2010
Table 4: RIDIT values and GRA grades
S. no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
RID IT
Scaled items
values
It's “pric e” is a fford able
0.397
I rely o n N ano as it is a “ Tata Pro duc t”
0.444
I love the name "Nano"
0.448
It is available in “attractive colors”
0.684
I love it's “style / look”
0.618
It has a “high fuel efficiency”
0.669
I am satisfied with the “financing option” 0.755
I like its “interior design”
0.518
Overall it is a “comfortable” car
0.501
The “space inside” Nano surprised me
0.383
Ov erall I w ill be v ery h app y to
0.447
possess a Nano
Overall it is “value for money”
0.227
Features of this car fulfils my
0.419
requ irem ents
It is an “environment friendly” car
0.436
I believe it's “running cost” will be low 0.553
The “w arranty” o ffered is satisfa ctory
0.680
I liked its “po wer”
0.560
It will add to my “status / prestige
0.464
It has proper “safety features”
0.246
I feel it will have a good “resale value” 0.313
There are adequate “accessories”
0.627
ava ilable
Test drive “performan ce” was o f
0.452
high standards
The findings have been sorted as warranted by the
respective analysis (Ch ien-Ho, 2007), so as to co mpare
the rankin gs of the scale items for their degree of
impo rtance or agreeme nt.
It is observed that there is positive correlation
between the two methods used for prioritizing the factors.
It is interesting to observe from the Table 5 that 16 out of
22 ranks as assigned by two techniques are matching. The
Table 5 shows that the top most reason for selecting to
book a TA TA Nano based on the finding s is its price. It is
followed closely by the fact that it is a T AT A product.
The third importan t reason is the name N ano seem s to
have caught the imagination of the consumer. The least
important reason for selection of the car being, “it’s test
drive perform ance ”. This can b e taken it is also another
indica tion for the correctness of the findings for none of
the customers had the opportunity of test-driving the
vehicle. The respondents had only got to view the vehicle
in the show room.
Rest of the items constitute three clusters i.e. cluster
one (consisting of items 10, 1, 13, 14, 2, 11, 3, 22, 18 can
be referred to as first hand overall perception of the
vehicle); cluster two (consisting of items 9, 8, 15, 17 can
be referred to as perception of performance promised) and
cluster three (consisting of items 5, 21, 6, 16, 4 can be
referred to as perception about real performance of the
TATA Nano post purchase). These three fall the same
order betw een the top three reasons and the least
important reason for selecting TATA N ano. Based on the
ranking we may infer that next to the top three reasons for
selecting the car is cluster o ne i.e. the first hand overa ll
perce ption about the vehicle.
GRA
grades
0.760
0.717
0.729
0.546
0.588
0.550
0.496
0.665
0.679
0.765
0.720
0.920
0.745
0.731
0.641
0.552
0.631
0.706
0.909
0.843
0.589
0.717
developing state in Eastern part of India. The
demographic profile of the sample is shown in Table 3.
Using the algorithms furnished in the App endix A -B
respectively the RIDIT values and the GRA grades were
calculated for each of the scale items and is shown in
Table 4 along with 22 parameters used.
Table 5: RIDIT and GRA comparative ranking
Sr No.
Scaled items
RIDIT values
1
It's “pric e” is a fford able
0.227
2
I rely o n N ano as it is a “ Tata pro duc t”
0.246
3
I love the name "Nano"
0.313
4
It is available in “attractive colors”
0.383
5
I love it's “style / look”
0.397
6
It has a “high fuel efficiency”
0.419
7
I am satisfied with the “financing option”
0.436
8
I like its “interior design”
0.444
9
Overall it is a “comfortable” car
0.447
10
The “space inside” Nano surprised me
0.448
11
Overall I will be very happy to possess a Nano
0.452
12
Overall it is “value for money”
0.464
13
Fea tures of th is car f ulfils m y req uirem ents
0.501
14
It is an “environment friendly” car
0.518
15
I believe it's “running cost” will be low
0.553
16
The “w arranty” o ffered is satisfa ctory
0.560
17
I liked its “po wer”
0.618
18
It will add to my “status / prestige
0.627
19
It has proper “safety features”
0.669
20
I feel it will have a good “resale value”
0.680
21
Th ere are ade qua te “ac cess ories ” av ailab le
0.684
22
Test drive “performance” was of high standards
0.755
Spearman Rank Order Correlations between RIDIT rank and GRA rank is 0.596838
53
RIDIT rank
GRA grades
12
0.920
19
0.909
20
0.843
10
0.765
1
0.760
13
0.745
14
0.731
2
0.729
11
0.720
3
0.717
22
0.717
18
0.706
9
0.679
8
0.665
15
0.641
17
0.631
5
0.589
21
0.588
6
0.552
16
0.550
4
0.546
7
0.496
which is significant at p<05000
GRA rank
12
19
20
10
1
13
14
3
11
2
22
18
9
8
15
17
21
5
16
6
4
7
Asian J. Bus. Manage., 2(3): 48-56, 2010
CONCLUSION
As per Cygnus R esearch (2009) report among the
manufacturing industries, automobiles witnessed highest
grow th followed by steel. Automobiles led to strong
demand due to signs of revival in economy and increasing
trend in hiring especially in IT sector and cheaper bank
credit. In this context Tata Motors strategy of producing
of people’s car for India is rightly timed. The project is
the realization of dream of Ratan Tata Chairm an of T ata
groups to provide car to common men of India. The study
carried out intends to have an insight into prospective
consum ers mind for the ca r Nano . A total of 22 factors
have been identified through literature review and these
factors are prioritized with reference to the small car
Nano. The finding of the study shows that price of the car
is most important factor for selecting Nano followed by
the name TATA which stan d quite tall in the country. The
colour variant, style, fuel efficiency and financing option
offered by the company are other important factors which
attract the customers towards the car. Pow er, safety
feature, prestige involv ed, resale value of the car etc. are
some of the features which ranks low in the priority of the
consumers.
2)
Co mp ute ridits and mean ridits for compa rison data sets. Note that
a comparison data set is comprised of the frequencies of responses
for each category of a Likert scale item. Since there are m Likert
scale items in this illustration, there will be m comparison data
sets.
C
Comp ute ridit value rij for each category of scale items.
Bij is the frequency of category j for the ith scale item, and Bi is a
short form for the summation of frequencies for scale item i across
all categories, i.e.
C
Co mp ute m ean ridit Di for each Likert scale item.
C
Co mp ute confid ence in terval for Di. Wh en the size of the reference
data set is very large relative to that of any comparison data set, the
95% confidence interval of any Di is:
C
Test the following hypothesis using Kruskal-Wallis statistics W .
A p p en d ix A :
Algorithm for RIDIT Analysis (Ch ien-Ho, 200 7): Suppo se that there are
m items and n ordered categories listed from the most favoured to the
least favoured in the scale, and then R IDIT analysis go es as follows.
1)
C
C
C
Co mp ute rid its for th e refe renc e da ta set.
Select a pop ulation to serve as a referenc e data se t. For a Lik ert
scale survey, the reference data set can be the total responses of the
survey, if the population cannot be easily identified.
Co mp ute frequency fj for each category of responses, where j =1,
..., n
Co mp ute mid-point accumulated frequency Fj for each category of
responses.
W follows a P2 distribution wi th ( m -1) deg ree of free dom . If H 0
cannot be accepted, examine the relationships among confidence
interv als of D. The general rules for interpreting the values of D are
s ho w n b el ow .
C
B
Co mp ute ridit value Rj for each category of responses in the
refere nce data set.
B
N is the to tal nu mb er of r esp ons es fro m th e Lik ert sca le survey of
intere st. By definition, the expected v alue of R for the reference
data set is always 0.5.
B
54
A scale item with its Di valu e statistic ally dev iate from 0.5 implies
a significant difference in the response patterns between the
reference data set and the comparison data set for the particular
scale item. If the confidence interval of a Di con tains 0 .5, then it is
accepted that the Di value is not significantly deviate from 0.5.
A l ow valu e of Di is preferred over a high value o f Di because a
low value o f Di indicates a low probability of being in a negative
propensity.
The response patterns of scale items with overlapped confidence
interv als of D are co nsid ered , amo ng th e resp ond ents , to be
statistically indifferen t from ea ch oth er.
Asian J. Bus. Manage., 2(3): 48-56, 2010
A p p en d ix B :
A proce dure fo r the grey relational an alysis, wh ich is app ropriate for
Lik ert scale data analysis, consists of the following steps (ChienHo , 2007 ).
C
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C
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